'Breast cancer research is always working to improve. Researchers have come up with a cutting edge system. Simulations using polarized Monte Carlo methods enhance the clarity of tissue structures. '

'Experiments run aimed at detecting tumours at the edges where you'd guess thick slices of the tissue might show problems post surgery. 'The simulation software used gives more details and makes the differences in the tissue clearer with comparisons made to permission standard microscopy. It does so by adding layers of special light contrasts. '

'The challenge is to see the ones hidden. So, a Convolutional Neural Network (CNN) was pressed into service, which looks out for nine specific positions in relation to light sources and even finds tumours outside of illuminated areas. ''

The goal is a system capable of processing images in real-time. This mimics a live diagnostic case for a test tumor.

'Better high-tech tools and real-time data could just work to stay ahead in minute by minute diagnoses broken down into tiny parts using compermental techniques that allows hug-e processing power upsizes. '

The real clincher gives you a confident chance to recognize accurately any tumors at 96% accuracy threshold. This is only a baseline and improvable the deductions post- Finishing tests were also done with real tissue models taken from the lab which scored a whopping 100% in targeted spots'

 unlike current methods these tests done in vitro

Lifting the Lid on Hidden Tumours: Tech and Cancer Research

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